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Cuffless blood pressure estimation algorithms for continuous health-care monitoring

Kachuee, M ; Sharif University of Technology | 2017

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  1. Type of Document: Article
  2. DOI: 10.1109/TBME.2016.2580904
  3. Publisher: IEEE Computer Society , 2017
  4. Abstract:
  5. Goal: Continuous blood pressure (BP) monitoring can provide invaluable information about individuals' health conditions. However, BP is conventionally measured using inconvenient cuff-based instruments, which prevents continuous BP monitoring. This paper presents an efficient algorithm, based on the pulse arrival time (PAT), for the continuous and cuffless estimation of the systolic BP, diastolic blood pressure (DBP), and mean arterial pressure (MAP) values. Methods: The proposed framework estimates the BP values through processing vital signals and extracting two types of features, which are based on either physiological parameters or whole-based representation of vital signals. Finally, the regression algorithms are employed for the BP estimation. Although the proposed algorithm works reliably without any need for calibration, an optional calibration procedure is also suggested, which can improve the system's accuracy even further. Results: The proposed method is evaluated on about a thousand subjects using the Association for the Advancement of Medical Instrumentation (AAMI) and the British Hypertension Society (BHS) standards. The method complies with the AAMI standard in the estimation of DBP and MAP values. Regarding the BHS protocol, the results achieve grade A for the estimation of DBP and grade B for the estimation of MAP. Conclusion: We conclude that by using the PAT in combination with informative features from the vital signals, the BP can be accurately and reliably estimated in a noninvasive fashion. Significance: The results indicate that the proposed algorithm for the cuffless estimation of the BP can potentially enable mobile health-care gadgets to monitor the BP continuously. © 1964-2012 IEEE
  6. Keywords:
  7. Blood pressure ; Electrocardiograph (ECG) ; Mobile health ; photoplethysmograph (PPG) ; pulse arrival time (PAT) ; Calibration ; Health care ; MHealth ; Physiological models ; Signal processing ; Blood pressure estimation ; Diastolic blood pressures ; Mean arterial pressure ; Medical instrumentation ; Photoplethysmograph ; Physiological parameters ; Pulse arrival time ; Algorithm ; Article ; Blood pressure monitoring ; Diastolic blood pressure ; Human ; Pulse rate ; Systolic blood pressure ; Time ; Ambulatory monitoring ; Blood pressure measurement ; Blood pressure monitor ; Computer assisted diagnosis ; Device failure analysis ; Devices ; Evaluation study ; Physiology ; Procedures ; Pulse wave ; Reproducibility ; Validation study ; Algorithms ; Blood Pressure Determination ; Blood Pressure Monitors ; Diagnosis, Computer-Assisted ; Equipment Design ; Equipment Failure Analysis ; Humans ; Machine Learning ; Monitoring, Ambulatory ; Pulse Wave Analysis ; Reproducibility of Results ; Sensitivity and Specificity
  8. Source: IEEE Transactions on Biomedical Engineering ; Volume 64, Issue 4 , 2017 , Pages 859-869 ; 00189294 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/7491263